
import numpy as np
from scipy import signal

x = np.linspace(0, 0.999, 1000)
tau0 = x[1] - x[0]
fs = 1/tau0
N = len(x)


# import matplotlib.pyplot as plt
# f = 10
# phi = 0
# # sig = np.cos(2*np.pi*f*x + phi)
# sig = (np.cos(2*np.pi*f*x)+1)
# profile = signal.gaussian(N, std=N/10)
# final = sig * profile
# # sig = [i+np.random.rand()/5 for i in sig]
# plt.figure(1)
# plt.subplot(3,1,1)
# plt.plot(sig)
# plt.subplot(3,1,2)
# plt.plot(profile)
# plt.subplot(3,1,3)
# plt.plot(final)
# plt.show()